Static endpoint validation

ABSTRACT

Systems, methods, and computer-readable media are disclosed for validating endpoint information for nodes in a network. A network assurance appliance is configured to retrieve a configured static endpoint information in a logical model of a network from a network controller and connected static endpoint information from one or more nodes in the network. The network assurance appliance determines that there is an inconsistency based on a comparison of the configured static endpoint information and the connected static endpoint information and generating an event specifying the inconsistency.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. provisional patent application62/521,693, filed on Jun. 19, 2017, “STATIC ENDPOINT VALIDATION,” thecontents of which are herein incorporated by reference in its entirety.

TECHNICAL FIELD

The present technology pertains to network configuration assurance andtroubleshooting, and more specifically to validating endpointinformation for nodes in a network.

BACKGROUND

Network configurations for large data center networks are oftenspecified at a centralized controller. The controller can programswitches, routers, servers, and elements in the network according to thespecified network configurations. Network configurations are inherentlyvery complex, and involve low level as well as high level configurationsof several layers of the network such as access policies, forwardingpolicies, routing policies, security policies, QoS policies, etc. Givensuch complexity, the network configuration process is error prone. Inmany cases, the configurations defined on a controller, which canreflect an intent specification for the network, can contain errors andinconsistencies that are often extremely difficult to identify and maycreate significant problems in the network.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary embodiments of the disclosure and are nottherefore to be considered to be limiting of its scope, the principlesherein are described and explained with additional specificity anddetail through the use of the accompanying drawings in which:

FIGS. 1A and 1B illustrate example network environments, in accordancewith various aspects of the subject technology;

FIG. 2A illustrates an example object model for a network, in accordancewith various aspects of the subject technology;

FIG. 2B illustrates an example object model for a tenant object in theexample object model from FIG. 2A, in accordance with various aspects ofthe subject technology;

FIG. 2C illustrates an example association of various objects in theexample object model from FIG. 2A, in accordance with various aspects ofthe subject technology;

FIG. 2D illustrates a schematic diagram of example models forimplementing the example object model from FIG. 2A, in accordance withvarious aspects of the subject technology;

FIG. 3A illustrates an example network assurance appliance, inaccordance with various aspects of the subject technology;

FIG. 3B illustrates an example system for network assurance, inaccordance with various aspects of the subject technology;

FIG. 3C illustrates a schematic diagram of an example system for staticpolicy analysis in a network, in accordance with various aspects of thesubject technology;

FIG. 4 illustrates an example method embodiment for network assurance,in accordance with various aspects of the subject technology;

FIG. 5 illustrates an example network environment, in accordance withvarious aspects of the subject technology;

FIG. 6 illustrates an example method embodiment for validating anendpoint configuration between nodes, in accordance with various aspectsof the subject technology;

FIG. 7 illustrates an example method embodiment for validating anendpoint configuration between nodes, in accordance with various aspectsof the subject technology;

FIG. 8 illustrates an example method embodiment for static endpointvalidation, in accordance with various aspects of the subjecttechnology;

FIG. 9 illustrates an example method embodiment for static endpointvalidation, in accordance with various aspects of the subjecttechnology;

FIGS. 10A-10F illustrate example user interfaces, in accordance withvarious aspects of the subject technology;

FIG. 11 illustrates an example network device in accordance with variousembodiments; and

FIG. 12 illustrates an example computing device in accordance withvarious embodiments.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Various embodiments of the disclosure are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the disclosure.Thus, the following description and drawings are illustrative and arenot to be construed as limiting. Numerous specific details are describedto provide a thorough understanding of the disclosure. However, incertain instances, well-known or conventional details are not describedin order to avoid obscuring the description. References to one or anembodiment in the present disclosure can be references to the sameembodiment or any embodiment; and, such references mean at least one ofthe embodiments.

Reference to “one embodiment” or “an embodiment” means that a particularfeature, structure, or characteristic described in connection with theembodiment is included in at least one embodiment of the disclosure. Theappearances of the phrase “in one embodiment” in various places in thespecification are not necessarily all referring to the same embodiment,nor are separate or alternative embodiments mutually exclusive of otherembodiments. Moreover, various features are described which may beexhibited by some embodiments and not by others.

The terms used in this specification generally have their ordinarymeanings in the art, within the context of the disclosure, and in thespecific context where each term is used. Alternative language andsynonyms may be used for any one or more of the terms discussed herein,and no special significance should be placed upon whether or not a termis elaborated or discussed herein. In some cases, synonyms for certainterms are provided. A recital of one or more synonyms does not excludethe use of other synonyms. The use of examples anywhere in thisspecification including examples of any terms discussed herein isillustrative only, and is not intended to further limit the scope andmeaning of the disclosure or of any example term. Likewise, thedisclosure is not limited to various embodiments given in thisspecification.

Without intent to limit the scope of the disclosure, examples ofinstruments, apparatus, methods, and their related results according tothe embodiments of the present disclosure are given below. Note thattitles or subtitles may be used in the examples for convenience of areader, which in no way should limit the scope of the disclosure. Unlessotherwise defined, technical, and scientific terms used herein have themeaning as commonly understood by one of ordinary skill in the art towhich this disclosure pertains. In the case of conflict, the presentdocument, including definitions will control.

Additional features and advantages of the disclosure will be set forthin the description which follows, and in part will be obvious from thedescription, or can be learned by practice of the herein disclosedprinciples. The features and advantages of the disclosure can berealized and obtained by means of the instruments and combinationsparticularly pointed out in the appended claims. These and otherfeatures of the disclosure will become more fully apparent from thefollowing description and appended claims, or can be learned by thepractice of the principles set forth herein.

Overview

Disclosed herein are systems, methods, and computer-readable media fornetwork configuration, troubleshooting, and validating endpointinformation for nodes in a network. A network assurance appliance isconfigured to retrieve a configured static endpoint information in alogical model of a network from a network controller and connectedstatic endpoint information from one or more nodes in the network. Thenetwork assurance appliance determines that there is an inconsistencybased on a comparison of the configured static endpoint information andthe connected static endpoint information and generating an eventspecifying the inconsistency.

Example Embodiments

The disclosed technology addresses the need in the art validatingendpoint information for nodes in a network. The present technology willbe described in the following disclosure as follows. The discussionbegins with an introductory discussion of network assurance and adescription of example computing environments, as illustrated in FIGS.1A and 1B. A discussion of network models for network assurance, asshown in FIGS. 2A through 2D, and network assurance systems and methodswill then follow. The discussion concludes with a description of anexample network device, as illustrated in FIG. 11, and an examplecomputing device, as illustrated in FIG. 12, including example hardwarecomponents suitable for hosting software applications and performingcomputing operations. The disclosure now turns to an introductorydiscussion of network assurance.

Network assurance is the guarantee or determination that the network isbehaving as intended by the network operator and has been configuredproperly (e.g., the network is doing what it is intended to do). Intentcan encompass various network operations, such as bridging, routing,security, service chaining, endpoints, compliance, QoS (Quality ofService), audits, etc. Intent can be embodied in one or more policies,settings, configurations, etc., defined for the network and individualnetwork elements (e.g., switches, routers, applications, resources,etc.). However, often times, the configurations, policies, etc., definedby a network operator are incorrect or not accurately reflected in theactual behavior of the network. For example, a network operatorspecifies a configuration A for one or more types of traffic but laterfinds out that the network is actually applying configuration B to thattraffic or otherwise processing that traffic in a manner that isinconsistent with configuration A. This can be a result of manydifferent causes, such as hardware errors, software bugs, varyingpriorities, configuration conflicts, misconfiguration of one or moresettings, improper rule rendering by devices, unexpected errors orevents, software upgrades, configuration changes, failures, etc. Asanother example, a network operator implements configuration C but oneor more other configurations result in the network behaving in a mannerthat is inconsistent with the intent reflected by the implementation ofconfiguration C. For example, such a situation can result whenconfiguration C conflicts with other configurations in the network.

The approaches herein can provide network assurance by modeling variousaspects of the network and/or performing consistency checks as well asother network assurance checks. The network assurance approaches hereincan be implemented in various types of networks, including a privatenetwork, such as a local area network (LAN); an enterprise network; astandalone or traditional network, such as a data center network; anetwork including a physical or underlay layer and a logical or overlaylayer, such as a virtual extensible LAN (VXLAN) or software-definednetwork (SDN) (e.g., Application Centric Infrastructure (ACI) or VMwareNSX networks); etc.

Network models can be constructed for a network and implemented fornetwork assurance. A network model can provide a representation of oneor more aspects of a network, including, without limitation thenetwork's policies, configurations, requirements, security, routing,topology, applications, hardware, filters, contracts, access controllists, infrastructure, etc. As will be further explained below,different types of models can be generated for a network.

Such models can be implemented to ensure that the behavior of thenetwork will be consistent (or is consistent) with the intended behaviorreflected through specific configurations (e.g., policies, settings,definitions, etc.) implemented by the network operator. Unliketraditional network monitoring, which involves sending and analyzingdata packets and observing network behavior, network assurance can beperformed through modeling without necessarily ingesting packet data ormonitoring traffic or network behavior. This can result in foresight,insight, and hindsight: problems can be prevented before they occur,identified when they occur, and fixed immediately after they occur.

Thus, network assurance can involve modeling properties of the networkto deterministically predict the behavior of the network. The networkcan be determined to be healthy if the model(s) indicate proper behavior(e.g., no inconsistencies, conflicts, errors, etc.). The network can bedetermined to be functional, but not fully healthy, if the modelingindicates proper behavior but some inconsistencies. The network can bedetermined to be non-functional and not healthy if the modelingindicates improper behavior and errors. If inconsistencies or errors aredetected by the modeling, a detailed analysis of the correspondingmodel(s) can allow one or more underlying or root problems to beidentified with great accuracy.

The modeling can consume numerous types of smart events which model alarge amount of behavioral aspects of the network. Smart events canimpact various aspects of the network, such as underlay services,overlay services, tenant connectivity, tenant security, tenant end point(EP) mobility, tenant policy, tenant routing, resources, etc.

Having described various aspects of network assurance, the disclosurenow turns to a discussion of example network environments for networkassurance.

FIG. 1A illustrates example network environments, in accordance withvarious aspects of the subject technology. In particular, FIG. 1Aillustrates a diagram of an example Network Environment 100, such as adata center. The Network Environment 100 can include a Fabric 120 whichcan represent the physical layer or infrastructure (e.g., underlay) ofthe Network Environment 100. Fabric 120 can include Spines 102 (e.g.,spine routers or switches) and Leafs 104 (e.g., leaf routers orswitches) which can be interconnected for routing or switching trafficin the Fabric 120. Spines 102 can interconnect Leafs 104 in the Fabric120, and Leafs 104 can connect the Fabric 120 to an overlay or logicalportion of the Network Environment 100, which can include applicationservices, servers, virtual machines, containers, endpoints, etc. Thus,network connectivity in the Fabric 120 can flow from Spines 102 to Leafs104, and vice versa. The interconnections between Leafs 104 and Spines102 can be redundant (e.g., multiple interconnections) to avoid afailure in routing. In some embodiments, Leafs 104 and Spines 102 can befully connected, such that any given Leaf is connected to each of theSpines 102, and any given Spine is connected to each of the Leafs 104.Leafs 104 can be, for example, top-of-rack (“ToR”) switches, aggregationswitches, gateways, ingress and/or egress switches, provider edgedevices, and/or any other type of routing or switching device.

Leafs 104 can be responsible for routing and/or bridging tenant orcustomer packets and applying network policies or rules. Networkpolicies and rules can be driven by one or more Controllers 116, and/orimplemented or enforced by one or more devices, such as Leafs 104. Leafs104 can connect other elements to the Fabric 120. For example, Leafs 104can connect Servers 106, Hypervisors 108, Virtual Machines (VMs) 110,Applications 112, Network Device 114, etc., with Fabric 120. Suchelements can reside in one or more logical or virtual layers ornetworks, such as an overlay network. In some cases, Leafs 104 canencapsulate and decapsulate packets to and from such elements (e.g.,Servers 106) in order to enable communications throughout NetworkEnvironment 100 and Fabric 120. Leafs 104 can also provide any otherdevices, services, tenants, or workloads with access to Fabric 120. Insome cases, Servers 106 connected to Leafs 104 can similarly encapsulateand decapsulate packets to and from Leafs 104. For example, Servers 106can include one or more virtual switches or routers or tunnel endpointsfor tunneling packets between an overlay or logical layer hosted by, orconnected to, Servers 106 and an underlay layer represented by Fabric120 and accessed via Leafs 104.

Applications 112 can include software applications, services,containers, appliances, functions, service chains, etc. For example,Applications 112 can include a firewall, a database, a content deliverynetwork (CDN) server, an intrusion defense system (IDS) or intrusionprevention system (IPS), a deep packet inspection service, a messagerouter, a virtual switch, etc. An application from Applications 112 canbe distributed, chained, or hosted by multiple endpoints (e.g., Servers106, VMs 110, etc.), or may run or execute entirely from a singleendpoint.

VMs 110 can be virtual machines hosted by Hypervisors 108 or virtualmachine managers running on Servers 106. VMs 110 can include workloadsrunning on a guest operating system on a respective server. Hypervisors108 can provide a layer of software, firmware, and/or hardware thatcreates, manages, and/or runs the VMs 110. Hypervisors 108 can allow VMs110 to share hardware resources on Servers 106, and the hardwareresources on Servers 106 to appear as multiple, separate hardwareplatforms. Moreover, Hypervisors 108 on Servers 106 can host one or moreVMs 110.

In some cases, VMs 110 and/or Hypervisors 108 can be migrated to otherServers 106. Servers 106 can similarly be migrated to other locations inNetwork Environment 100. For example, a server connected to a specificleaf can be changed to connect to a different or additional leaf. Suchconfiguration or deployment changes can involve modifications tosettings, configurations, and policies that are applied to the resourcesbeing migrated as well as other network components.

In some cases, one or more Servers 106, Hypervisors 108, and/or VMs 110can represent or reside in a tenant or customer space. Tenant space caninclude workloads, services, applications, devices, networks, and/orresources that are associated with one or more clients or subscribers.Accordingly, traffic in Network Environment 100 can be routed based onspecific tenant policies, spaces, agreements, configurations, etc.Moreover, addressing can vary between one or more tenants. In someconfigurations, tenant spaces can be divided into logical segmentsand/or networks and separated from logical segments and/or networksassociated with other tenants. Addressing, policy, security, andconfiguration information between tenants can be managed by Controllers116, Servers 106, Leafs 104, etc.

Configurations in Network Environment 100 can be implemented at alogical level, a hardware level (e.g., physical), and/or both. Forexample, configurations can be implemented at a logical and/or hardwarelevel based on endpoint or resource attributes, such as endpoint typesand/or application groups or profiles, through a software-definednetwork (SDN) framework (e.g., Application-Centric Infrastructure (ACI)or VMWARE NSX). To illustrate, one or more administrators can defineconfigurations at a logical level (e.g., application or software level)through Controllers 116, which can implement or propagate suchconfigurations through Network Environment 100. In some examples,Controllers 116 can be Application Policy Infrastructure Controllers(APICs) in an ACI framework. In other examples, Controllers 116 can beone or more management components for associated with other SDNsolutions, such as NSX Managers.

Such configurations can define rules, policies, priorities, protocols,attributes, objects, etc., for routing and/or classifying traffic inNetwork Environment 100. For example, such configurations can defineattributes and objects for classifying and processing traffic based onEndpoint Groups (EPGs), Security Groups (SGs), VM types, bridge domains(BDs), virtual routing and forwarding instances (VRFs), tenants,priorities, firewall rules, etc. Other example network objects andconfigurations are further described below. Traffic policies and rulescan be enforced based on tags, attributes, or other characteristics ofthe traffic, such as protocols associated with the traffic, EPGsassociated with the traffic, SGs associated with the traffic, networkaddress information associated with the traffic, etc. Such policies andrules can be enforced by one or more elements in Network Environment100, such as Leafs 104, Servers 106, Hypervisors 108, Controllers 116,etc. As previously explained, Network Environment 100 can be configuredaccording to one or more particular software-defined network (SDN)solutions, such as CISCO ACI or VMWARE NSX. These example SDN solutionsare briefly described below.

ACI can provide an application-centric or policy-based solution throughscalable distributed enforcement. ACI supports integration of physicaland virtual environments under a declarative configuration model fornetworks, servers, services, security, requirements, etc. For example,the ACI framework implements EPGs, which can include a collection ofendpoints or applications that share common configuration requirements,such as security, QoS, services, etc. Endpoints can be virtual/logicalor physical devices, such as VMs, containers, hosts, or physical serversthat are connected to Network Environment 100. Endpoints can have one ormore attributes such as a VM name, guest OS name, a security tag,application profile, etc. Application configurations can be appliedbetween EPGs, instead of endpoints directly, in the form of contracts.Leafs 104 can classify incoming traffic into different EPGs. Theclassification can be based on, for example, a network segmentidentifier such as a VLAN ID, VXLAN Network Identifier (VNID), NetworkVirtualization using Generic Routing Encapsulation (NVGRE) VirtualSubnet Identifier (VSID), MAC address, IP address, etc.

In some cases, classification in the ACI infrastructure can beimplemented by Application Virtual Switches (AVS), which can run on ahost, such as a server or switch. For example, an AVS can classifytraffic based on specified attributes, and tag packets of differentattribute EPGs with different identifiers, such as network segmentidentifiers (e.g., VLAN ID). Finally, Leafs 104 can tie packets withtheir attribute EPGs based on their identifiers and enforce policies,which can be implemented and/or managed by one or more Controllers 116.Leaf 104 can classify to which EPG the traffic from a host belongs andenforce policies accordingly.

Another example SDN solution is based on VMWARE NSX. With VMWARE NSX,hosts can run a distributed firewall (DFW) which can classify andprocess traffic. Consider a case where three types of VMs, namely,application, database, and web VMs, are put into a single layer-2network segment. Traffic protection can be provided within the networksegment based on the VM type. For example, HTTP traffic can be allowedamong web VMs, and disallowed between a web VM and an application ordatabase VM. To classify traffic and implement policies, VMWARE NSX canimplement security groups, which can be used to group the specific VMs(e.g., web VMs, application VMs, and database VMs). DFW rules can beconfigured to implement policies for the specific security groups. Toillustrate, in the context of the previous example, DFW rules can beconfigured to block HTTP traffic between web, application, and databasesecurity groups.

Returning now to FIG. 1A, Network Environment 100 can deploy differenthosts via Leafs 104, Servers 106, Hypervisors 108, VMs 110, Applications112, and Controllers 116, such as VMWARE ESXi hosts, WINDOWS HYPER-Vhosts, bare metal physical hosts, etc. Network Environment 100 mayinteroperate with a variety of Hypervisors 108, Servers 106 (e.g.,physical and/or virtual servers), SDN orchestration platforms, etc.Network Environment 100 may implement a declarative model to allow itsintegration with application design and holistic network policy.

Controllers 116 can provide centralized access to fabric information,application configuration, resource configuration, application-levelconfiguration modeling for a software-defined network (SDN)infrastructure, integration with management systems or servers, etc.Controllers 116 can form a control plane that interfaces with anapplication plane via northbound APIs and a data plane via southboundAPIs.

As previously noted, Controllers 116 can define and manageapplication-level model(s) for configurations in Network Environment100. In some cases, application or device configurations can also bemanaged and/or defined by other components in the network. For example,a hypervisor or virtual appliance, such as a VM or container, can run aserver or management tool to manage software and services in NetworkEnvironment 100, including configurations and settings for virtualappliances.

As illustrated above, Network Environment 100 can include one or moredifferent types of SDN solutions, hosts, etc. For the sake of clarityand explanation purposes, various examples in the disclosure will bedescribed with reference to an ACI framework, and Controllers 116 may beinterchangeably referenced as controllers, APICs, or APIC controllers.However, it should be noted that the technologies and concepts hereinare not limited to ACI solutions and may be implemented in otherarchitectures and scenarios, including other SDN solutions as well asother types of networks which may not deploy an SDN solution.

Further, as referenced herein, the term “hosts” can refer to Servers 106(e.g., physical or logical), Hypervisors 108, VMs 110, containers (e.g.,Applications 112), etc., and can run or include any type of server orapplication solution. Non-limiting examples of “hosts” can includevirtual switches or routers, such as distributed virtual switches (DVS),application virtual switches (AVS), vector packet processing (VPP)switches; VCENTER and NSX MANAGERS; bare metal physical hosts; HYPER-Vhosts; VMs; DOCKER Containers; etc.

FIG. 1B illustrates example network environments, in accordance withvarious aspects of the subject technology. In particular, FIG. 1Billustrates another example of Network Environment 100. In this example,Network Environment 100 includes Endpoints 122 connected to Leafs 104 inFabric 120. Endpoints 122 can be physical and/or logical or virtualentities, such as servers, clients, VMs, hypervisors, softwarecontainers, applications, resources, network devices, workloads, etc.For example, an Endpoint 122 can be an object that represents a physicaldevice (e.g., server, client, switch, etc.), an application (e.g., webapplication, database application, etc.), a logical or virtual resource(e.g., a virtual switch, a virtual service appliance, a virtualizednetwork function (VNF), a VM, a service chain, etc.), a containerrunning a software resource (e.g., an application, an appliance, a VNF,a service chain, etc.), storage, a workload or workload engine, etc.Endpoints 122 can have an address (e.g., an identity), a location (e.g.,host, network segment, virtual routing and forwarding (VRF) instance,domain, etc.), one or more attributes (e.g., name, type, version, patchlevel, OS name, OS type, etc.), a tag (e.g., security tag), a profile,etc.

Endpoints 122 can be associated with respective Logical Groups 118.Logical Groups 118 can be logical entities containing endpoints(physical and/or logical or virtual) grouped together according to oneor more attributes, such as endpoint type (e.g., VM type, workload type,application type, etc.), one or more requirements (e.g., policyrequirements, security requirements, QoS requirements, customerrequirements, resource requirements, etc.), a resource name (e.g., VMname, application name, etc.), a profile, platform or operating system(OS) characteristics (e.g., OS type or name including guest and/or hostOS, etc.), an associated network or tenant, one or more policies, a tag,etc. For example, a logical group can be an object representing acollection of endpoints grouped together. To illustrate, Logical Group 1can contain client endpoints, Logical Group 2 can contain web serverendpoints, Logical Group 3 can contain application server endpoints,Logical Group N can contain database server endpoints, etc. In someexamples, Logical Groups 118 are EPGs in an ACI environment and/or otherlogical groups (e.g., SGs) in another SDN environment.

Traffic to and/or from Endpoints 122 can be classified, processed,managed, etc., based Logical Groups 118. For example, Logical Groups 118can be used to classify traffic to or from Endpoints 122, apply policiesto traffic to or from Endpoints 122, define relationships betweenEndpoints 122, define roles of Endpoints 122 (e.g., whether an endpointconsumes or provides a service, etc.), apply rules to traffic to or fromEndpoints 122, apply filters or access control lists (ACLs) to trafficto or from Endpoints 122, define communication paths for traffic to orfrom Endpoints 122, enforce requirements associated with Endpoints 122,implement security and other configurations associated with Endpoints122, etc.

In an ACI environment, Logical Groups 118 can be EPGs used to definecontracts in the ACI. Contracts can include rules specifying what andhow communications between EPGs take place. For example, a contract candefine what provides a service, what consumes a service, and what policyobjects are related to that consumption relationship. A contract caninclude a policy that defines the communication path and all relatedelements of a communication or relationship between endpoints or EPGs.For example, a Web EPG can provide a service that a Client EPG consumes,and that consumption can be subject to a filter (ACL) and a servicegraph that includes one or more services, such as firewall inspectionservices and server load balancing.

FIG. 2A illustrates an example object model for a network, in accordancewith various aspects of the subject technology. In particular, FIG. 2Aillustrates a diagram of an example Management Information Model 200 foran SDN network, such as Network Environment 100. The followingdiscussion of Management Information Model 200 references various termswhich shall also be used throughout the disclosure. Accordingly, forclarity, the disclosure shall first provide below a list of terminology,which will be followed by a more detailed discussion of ManagementInformation Model 200.

As used herein, an “Alias” can refer to a changeable name for a givenobject. Thus, even if the name of an object, once created, cannot bechanged, the Alias can be a field that can be changed.

As used herein, the term “Aliasing” can refer to a rule (e.g.,contracts, policies, configurations, etc.) that overlaps one or moreother rules. For example, Contract 1 defined in a logical model of anetwork can be said to be aliasing Contract 2 defined in the logicalmodel of the network if Contract 1 overlaps Contract 1. In this example,by aliasing Contract 2, Contract 1 may render Contract 2 redundant orinoperable. For example, if Contract 1 has a higher priority thanContract 2, such aliasing can render Contract 2 redundant based onContract 1's overlapping and higher priority characteristics.

As used herein, the term “APIC” can refer to one or more controllers(e.g., Controllers 116) in an ACI framework. The APIC can provide aunified point of automation and management, policy programming,application deployment, health monitoring for an ACI multitenant fabric.The APIC can be implemented as a single controller, a distributedcontroller, or a replicated, synchronized, and/or clustered controller.

As used herein, the term “BDD” can refer to a binary decision tree. Abinary decision tree can be a data structure representing functions,such as Boolean functions.

As used herein, the term “BD” can refer to a bridge domain. A bridgedomain can be a set of logical ports that share the same flooding orbroadcast characteristics. Like a virtual LAN (VLAN), bridge domains canspan multiple devices. A bridge domain can be a L2 (Layer 2) construct.

As used herein, a “Consumer” can refer to an endpoint, resource, and/orEPG that consumes a service.

As used herein, a “Context” can refer to an L3 (Layer 3) address domainthat allows multiple instances of a routing table to exist and worksimultaneously. This increases functionality by allowing network pathsto be segmented without using multiple devices. Non-limiting examples ofa context or L3 address domain can include a Virtual Routing andForwarding (VRF) instance, a private network, and so forth.

As used herein, the term “Contract” can refer to rules or configurationsthat specify what and how communications in a network are conducted(e.g., allowed, denied, filtered, processed, etc.). In an ACI network,contracts can specify how communications between endpoints and/or EPGstake place. In some examples, a contract can provide rules andconfigurations akin to an Access Control List (ACL).

As used herein, the term “Distinguished Name” (DN) can refer to a uniquename that describes an object, such as an MO, and locates its place inManagement Information Model 200. In some cases, the DN can be (orequate to) a Fully Qualified Domain Name (FQDN).

As used herein, the term “Endpoint Group” (EPG) can refer to a logicalentity or object associated with a collection or group of endpoints aspreviously described with reference to FIG. 1B.

As used herein, the term “Filter” can refer to a parameter orconfiguration for allowing communications. For example, in a whitelistmodel where all communications are blocked by default, a communicationmust be given explicit permission to prevent such communication frombeing blocked. A filter can define permission(s) for one or morecommunications or packets. A filter can thus function similar to an ACLor Firewall rule. In some examples, a filter can be implemented in apacket (e.g., TCP/IP) header field, such as L3 protocol type, L4 (Layer4) ports, and so on, which is used to allow inbound or outboundcommunications between endpoints or EPGs, for example.

As used herein, the term “L2 Out” can refer to a bridged connection. Abridged connection can connect two or more segments of the same networkso that they can communicate. In an ACI framework, an L2 out can be abridged (Layer 2) connection between an ACI fabric (e.g., Fabric 120)and an outside Layer 2 network, such as a switch.

As used herein, the term “L3 Out” can refer to a routed connection. Arouted Layer 3 connection uses a set of protocols that determine thepath that data follows in order to travel across networks from itssource to its destination. Routed connections can perform forwarding(e.g., IP forwarding) according to a protocol selected, such as BGP(border gateway protocol), OSPF (Open Shortest Path First), EIGRP(Enhanced Interior Gateway Routing Protocol), etc.

As used herein, the term “Managed Object” (MO) can refer to an abstractrepresentation of objects that are managed in a network (e.g., NetworkEnvironment 100). The objects can be concrete objects (e.g., a switch,server, adapter, etc.), or logical objects (e.g., an applicationprofile, an EPG, a fault, etc.). The MOs can be network resources orelements that are managed in the network. For example, in an ACIenvironment, an MO can include an abstraction of an ACI fabric (e.g.,Fabric 120) resource.

As used herein, the term “Management Information Tree” (MIT) can referto a hierarchical management information tree containing the MOs of asystem. For example, in ACI, the MIT contains the MOs of the ACI fabric(e.g., Fabric 120). The MIT can also be referred to as a ManagementInformation Model (MIM), such as Management Information Model 200.

As used herein, the term “Policy” can refer to one or morespecifications for controlling some aspect of system or networkbehavior. For example, a policy can include a named entity that containsspecifications for controlling some aspect of system behavior. Toillustrate, a Layer 3 Outside Network Policy can contain the BGPprotocol to enable BGP routing functions when connecting Fabric 120 toan outside Layer 3 network.

As used herein, the term “Profile” can refer to the configurationdetails associated with a policy. For example, a profile can include anamed entity that contains the configuration details for implementingone or more instances of a policy. To illustrate, a switch node profilefor a routing policy can contain the switch-specific configurationdetails to implement the BGP routing protocol.

As used herein, the term “Provider” refers to an object or entityproviding a service. For example, a provider can be an EPG that providesa service.

As used herein, the term “Subject” refers to one or more parameters in acontract for defining communications. For example, in ACI, subjects in acontract can specify what information can be communicated and how.Subjects can function similar to ACLs.

As used herein, the term “Tenant” refers to a unit of isolation in anetwork. For example, a tenant can be a secure and exclusive virtualcomputing environment. In ACI, a tenant can be a unit of isolation froma policy perspective, but does not necessarily represent a privatenetwork. Indeed, ACI tenants can contain multiple private networks(e.g., VRFs). Tenants can represent a customer in a service providersetting, an organization or domain in an enterprise setting, or just agrouping of policies.

As used herein, the term “VRF” refers to a virtual routing andforwarding instance. The VRF can define a Layer 3 address domain thatallows multiple instances of a routing table to exist and worksimultaneously. This increases functionality by allowing network pathsto be segmented without using multiple devices. Also known as a contextor private network.

Having described various terms used herein, the disclosure now returnsto a discussion of Management Information Model (MIM) 200 in FIG. 2A. Aspreviously noted, MIM 200 can be a hierarchical management informationtree or MIT. Moreover, MIM 200 can be managed and processed byControllers 116, such as APICs in an ACI. Controllers 116 can enable thecontrol of managed resources by presenting their manageablecharacteristics as object properties that can be inherited according tothe location of the object within the hierarchical structure of themodel.

The hierarchical structure of MIM 200 starts with Policy Universe 202 atthe top (Root) and contains parent and child nodes 116, 204, 206, 208,210, 212. Nodes 116, 202, 204, 206, 208, 210, 212 in the tree representthe managed objects (MOs) or groups of objects. Each object in thefabric (e.g., Fabric 120) has a unique distinguished name (DN) thatdescribes the object and locates its place in the tree. The Nodes 116,202, 204, 206, 208, 210, 212 can include the various MOs, as describedbelow, which contain policies that govern the operation of the system.

Controllers 116

Controllers 116 (e.g., APIC controllers) can provide management, policyprogramming, application deployment, and health monitoring for Fabric120.

Node 204

Node 204 includes a tenant container for policies that enable anadministrator to exercise domain-based access control. Non-limitingexamples of tenants can include:

User tenants defined by the administrator according to the needs ofusers. They contain policies that govern the operation of resources suchas applications, databases, web servers, network-attached storage,virtual machines, and so on.

The common tenant is provided by the system but can be configured by theadministrator. It contains policies that govern the operation ofresources accessible to all tenants, such as firewalls, load balancers,Layer 4 to Layer 7 services, intrusion detection appliances, and so on.

The infrastructure tenant is provided by the system but can beconfigured by the administrator. It contains policies that govern theoperation of infrastructure resources such as the fabric overlay (e.g.,VXLAN). It also enables a fabric provider to selectively deployresources to one or more user tenants. Infrastructure tenant polices canbe configurable by the administrator.

The management tenant is provided by the system but can be configured bythe administrator. It contains policies that govern the operation offabric management functions used for in-band and out-of-bandconfiguration of fabric nodes. The management tenant contains a privateout-of-bound address space for the Controller/Fabric internalcommunications that is outside the fabric data path that provides accessthrough the management port of the switches. The management tenantenables discovery and automation of communications with virtual machinecontrollers.

Node 206

Node 206 can contain access policies that govern the operation of switchaccess ports that provide connectivity to resources such as storage,compute, Layer 2 and Layer 3 (bridged and routed) connectivity, virtualmachine hypervisors, Layer 4 to Layer 7 devices, and so on. If a tenantrequires interface configurations other than those provided in thedefault link, Cisco Discovery Protocol (CDP), Link Layer DiscoveryProtocol (LLDP), Link Aggregation Control Protocol (LACP), or SpanningTree Protocol (STP), an administrator can configure access policies toenable such configurations on the access ports of Leafs 104.

Node 206 can contain fabric policies that govern the operation of theswitch fabric ports, including such functions as Network Time Protocol(NTP) server synchronization, Intermediate System-to-Intermediate SystemProtocol (IS-IS), Border Gateway Protocol (BGP) route reflectors, DomainName System (DNS) and so on. The fabric MO contains objects such aspower supplies, fans, chassis, and so on.

Node 208

Node 208 can contain VM domains that group VM controllers with similarnetworking policy requirements. VM controllers can share virtual space(e.g., VLAN or VXLAN space) and application EPGs. Controllers 116communicate with the VM controller to publish network configurationssuch as port groups that are then applied to the virtual workloads.

Node 210

Node 210 can contain Layer 4 to Layer 7 service integration life cycleautomation framework that enables the system to dynamically respond whena service comes online or goes offline. Policies can provide servicedevice package and inventory management functions.

Node 212

Node 212 can contain access, authentication, and accounting (AAA)policies that govern user privileges, roles, and security domains ofFabric 120.

The hierarchical policy model can fit well with an API, such as a RESTAPI interface. When invoked, the API can read from or write to objectsin the MIT. URLs can map directly into distinguished names that identifyobjects in the MIT. Data in the MIT can be described as a self-containedstructured tree text document encoded in XML or JSON, for example.

FIG. 2B illustrates an example object model for a tenant object, inaccordance with various aspects of the subject technology. FIG. 2Bincludes an example object model 220 for a tenant portion of MIM 200. Aspreviously noted, a tenant is a logical container for applicationpolicies that enable an administrator to exercise domain-based accesscontrol. A tenant thus represents a unit of isolation from a policyperspective, but it does not necessarily represent a private network.Tenants can represent a customer in a service provider setting, anorganization, or domain in an enterprise setting, or just a convenientgrouping of policies. Moreover, tenants can be isolated from one anotheror can share resources.

Tenant portion 204A of MIM 200 can include various entities, and theentities in Tenant Portion 204A can inherit policies from parententities. Non-limiting examples of entities in Tenant Portion 204A caninclude Filters 240, Contracts 236, Outside Networks 222, Bridge Domains230, VRF Instances 234, and Application Profiles 224.

Bridge Domains 230 can include Subnets 232. Contracts 236 can includeSubjects 238. Application Profiles 224 can contain one or more EPGs 226.Some applications can contain multiple components. For example, ane-commerce application could require a web server, a database server,data located in a storage area network, and access to outside resourcesthat enable financial transactions. Application Profile 224 contains asmany (or as few) EPGs as necessary that are logically related toproviding the capabilities of an application.

EPG 226 can be organized in various ways, such as based on theapplication they provide, the function they provide (such asinfrastructure), where they are in the structure of the data center(such as DMZ), or whatever organizing principle that a fabric or tenantadministrator chooses to use.

EPGs in the fabric can contain various types of EPGs, such asapplication EPGs, Layer 2 external outside network instance EPGs, Layer3 external outside network instance EPGs, management EPGs forout-of-band or in-band access, etc. EPGs 226 can also contain Attributes228, such as encapsulation-based EPGs, IP-based EPGs, or MAC-based EPGs.

As previously mentioned, EPGs can contain endpoints (e.g., EPs 122) thathave common characteristics or attributes, such as common policyrequirements (e.g., security, virtual machine mobility (VMM), QoS, orLayer 4 to Layer 7 services). Rather than configure and manage endpointsindividually, they can be placed in an EPG and managed as a group.

Policies apply to EPGs, including the endpoints they contain. An EPG canbe statically configured by an administrator in Controllers 116, ordynamically configured by an automated system such as VCENTER orOPENSTACK.

To activate tenant policies in Tenant Portion 204A, fabric accesspolicies should be configured and associated with tenant policies.Access policies enable an administrator to configure other networkconfigurations, such as port channels and virtual port channels,protocols such as LLDP, CDP, or LACP, and features such as monitoring ordiagnostics.

FIG. 2C illustrates an example association of various objects, inaccordance with various aspects of the subject technology. Inparticular, FIG. 2C includes an example Association 260 of tenantentities and access entities in MIM 200. Policy Universe 202 containsTenant Portion 204A and Access Portion 206A. Thus, Tenant Portion 204Aand Access Portion 206A are associated through Policy Universe 202.

Access Portion 206A can contain fabric and infrastructure accesspolicies. Typically, in a policy model, EPGs are coupled with VLANs. Fortraffic to flow, an EPG is deployed on a leaf port with a VLAN in aphysical, VMM, L2 out, L3 out, or Fiber Channel domain, for example.

Access Portion 206A thus contains Domain Profile 236 which can define aphysical, VMM, L2 out, L3 out, or Fiber Channel domain, for example, tobe associated to the EPGs. Domain Profile 236 contains VLAN InstanceProfile 238 (e.g., VLAN pool) and Attacheable Access Entity Profile(AEP) 240, which are associated directly with application EPGs. The AEP240 deploys the associated application EPGs to the ports to which it isattached, and automates the task of assigning VLANs. While a large datacenter can have thousands of active VMs provisioned on hundreds ofVLANs, Fabric 120 can automatically assign VLAN IDs from VLAN pools.This saves time compared with trunking down VLANs in a traditional datacenter.

FIG. 2D illustrates a schematic diagram of example models forimplementing MIM 200. The network assurance models can include L_Model270A (Logical Model), LR_Model 270B (Logical Rendered Model or LogicalRuntime Model), Li_Model 272 (Logical Model for i), Ci_Model 274(Concrete model for i), and Hi_Model 276 (Hardware model or TCAM Modelfor i).

L_Model 270A is the logical representation of the objects and theirrelationships in MIM 200. L_Model 270A can be generated by Controllers116 based on configurations entered in Controllers 116 for the network,and thus represents the configurations of the network at Controllers116. This is the declaration of the “end-state” expression that isdesired when the elements of the network entities (e.g., applications)are connected and Fabric 120 is provisioned by Controllers 116. In otherwords, because L_Model 270A represents the configurations entered inControllers 116, including the objects and relationships in MIM 200, itcan also reflect the “intent” of the administrator: how theadministrator wants the network and network elements to behave.

LR_Model 270B is the abstract model expression that Controllers 116(e.g., APICs in ACI) resolve from L_Model 270A. LR_Model 270B can thusprovide the elemental configuration components that would be deliveredto the physical infrastructure (e.g., Fabric 120) to execute one or morepolicies. For example, LR_Model 270B can be delivered to Leafs 104 inFabric 120 to configure Leafs 104 for communication with attachedEndpoints 122.

Li_Model 272 is a switch-level or switch-specific model obtained fromLogical Model 270A and/or Resolved Model 270B. For example, Li_Model 272can represent the portion of L_Model 270A and/or LR_Model 270Bpertaining to a specific switch or router i. To illustrate, Li_Model 272L₁ can represent the portion of L_Model 270A and/or LR_Model 270Bpertaining to Leaf 1 (104). Thus, Li_Model 272 can be generated fromL_Model 270A and/or LR_Model 270B for one or more switch or routers(e.g., Leafs 104 and/or Spines 102) on Fabric 120.

Ci_Model 274 is the actual in-state configuration at the individualfabric member i (e.g., switch i). In other words, Ci_Model 274 is aswitch-level or switch-specific model that is based on Li_Model 272. Forexample, Controllers 116 can deliver Li_Model 272 to Leaf 1 (104). Leaf1 (104) can take Li_Model 272, which can be specific to Leaf 1 (104),and render the policies in Li_Model 272 into a concrete model, Ci_Model274, that runs on Leaf 1 (104). Leaf 1 (104) can render Li_Model 272 viathe OS on Leaf 1 (104), for example. Thus, Ci_Model 274 can be analogousto compiled software, as it is the form of Li_Model 272 that the switchOS at Leaf 1 (104) can execute.

Hi_Model 276 is also a switch-level or switch-specific model for switchi, but is based on Ci_Model 274 for switch i. Hi_Model 276 is the actualconfiguration (e.g., rules) stored or rendered on the hardware or memory(e.g., TCAM memory) at the individual fabric member i (e.g., switch i).For example, Hi_Model 276 can represent the configurations (e.g., rules)which Leaf 1 (104) stores or renders on the hardware (e.g., TCAM memory)of Leaf 1 (104) based on Ci_Model 274 at Leaf 1 (104). The switch OS atLeaf 1 (104) can render or execute Ci_Model 274, and Leaf 1 (104) canstore or render the configurations from Ci_Model in storage, such as thememory or TCAM at Leaf 1 (104). The configurations from Hi_Model 276stored or rendered by Leaf 1 (104) represent the configurations thatwill be implemented by Leaf 1 (104) when processing traffic.

While Models 272, 274, 276 are shown as device-specific models, similarmodels can be generated or aggregated for a collection of fabric members(e.g., Leafs 104 and/or Spines 102) in Fabric 120. When combined,device-specific models, such as Model 272, Model 274, and/or Model 276,can provide a representation of Fabric 120 that extends beyond aparticular device. For example, in some cases, Li_Model 272, Ci_Model272, and/or Hi_Model 272 associated with some or all individual fabricmembers (e.g., Leafs 104 and Spines 102) can be combined or aggregatedto generate one or more aggregated models based on the individual fabricmembers.

As referenced herein, the terms H Model, T Model, and TCAM Model can beused interchangeably to refer to a hardware model, such as Hi_Model 276.For example, Ti Model, Hi_Model and TCAMi Model may be usedinterchangeably to refer to Hi_Model 276.

Models 270A, 270B, 272, 274, 276 can provide representations of variousaspects of the network or various configuration stages for MIM 200. Forexample, one or more of Models 270A, 270B, 272, 274, 276 can be used togenerate Underlay Model 278 representing one or more aspects of Fabric120 (e.g., underlay topology, routing, etc.), Overlay Model 280representing one or more aspects of the overlay or logical segment(s) ofNetwork Environment 100 (e.g., COOP, MPBGP, tenants, VRFs, VLANs,VXLANs, virtual applications, VMs, hypervisors, virtual switching,etc.), Tenant Model 282 representing one or more aspects of Tenantportion 204A in MIM 200 (e.g., security, forwarding, service chaining,QoS, VRFs, BDs, Contracts, Filters, EPGs, subnets, etc.), ResourcesModel 284 representing one or more resources in Network Environment 100(e.g., storage, computing, VMs, port channels, physical elements, etc.),etc.

In general, L_Model 270A can be the high-level expression of what existsin the LR_Model 270B, which should be present on the concrete devices asCi_Model 274 and Hi_Model 276 expression. If there is any gap betweenthe models, there may be inconsistent configurations or problems.

FIG. 3A illustrates a diagram of an example Assurance Appliance 300 fornetwork assurance. In this example, Assurance Appliance 300 can includek VMs 110 operating in cluster mode. VMs are used in this example forexplanation purposes. However, it should be understood that otherconfigurations are also contemplated herein, such as use of containers,bare metal devices, Endpoints 122, or any other physical or logicalsystems. Moreover, while FIG. 3A illustrates a cluster modeconfiguration, other configurations are also contemplated herein, suchas a single mode configuration (e.g., single VM, container, or server)or a service chain for example.

Assurance Appliance 300 can run on one or more Servers 106, VMs 110,Hypervisors 108, EPs 122, Leafs 104, Controllers 116, or any othersystem or resource. For example, Assurance Appliance 300 can be alogical service or application running on one or more VMs 110 in NetworkEnvironment 100.

The Assurance Appliance 300 can include Data Framework 308, which can bebased on, for example, APACHE APEX and HADOOP. In some cases, assurancechecks can be written as individual operators that reside in DataFramework 308. This enables a natively horizontal scale-out architecturethat can scale to arbitrary number of switches in Fabric 120 (e.g., ACIfabric).

Assurance Appliance 300 can poll Fabric 120 at a configurableperiodicity (e.g., an epoch). The analysis workflow can be setup as aDAG (Directed Acyclic Graph) of Operators 310, where data flows from oneoperator to another and eventually results are generated and persistedto Database 302 for each interval (e.g., each epoch).

The north-tier implements API Server (e.g., APACHE Tomcat and Springframework) 304 and Web Server 306. A graphical user interface (GUI)interacts via the APIs exposed to the customer. These APIs can also beused by the customer to collect data from Assurance Appliance 300 forfurther integration into other tools.

Operators 310 in Data Framework 308 (e.g., APEX/Hadoop) can togethersupport assurance operations. Below are non-limiting examples ofassurance operations that can be performed by Assurance Appliance 300via Operators 310.

Security Policy Adherence

Assurance Appliance 300 can check to make sure the configurations orspecification from L_Model 270A, which may reflect the user's intent forthe network, including for example the security policies andcustomer-configured contracts, are correctly implemented and/or renderedin Li_Model 272, Ci_Model 274, and Hi_Model 276, and thus properlyimplemented and rendered by the fabric members (e.g., Leafs 104), andreport any errors, contract violations, or irregularities found.

Static Policy Analysis

Assurance Appliance 300 can check for issues in the specification of theuser's intent or intents (e.g., identify contradictory or conflictingpolicies in L_Model 270A).

TCAM Utilization

TCAM is a scarce resource in the fabric (e.g., Fabric 120). However,Assurance Appliance 300 can analyze the TCAM utilization by the networkdata (e.g., Longest Prefix Match (LPM) tables, routing tables, VLANtables, BGP updates, etc.), Contracts, Logical Groups 118 (e.g., EPGs),Tenants, Spines 102, Leafs 104, and other dimensions in NetworkEnvironment 100 and/or objects in MIM 200, to provide a network operatoror user visibility into the utilization of this scarce resource. Thiscan greatly help for planning and other optimization purposes.

Endpoint Checks

Assurance Appliance 300 can validate that the fabric (e.g., fabric 120)has no inconsistencies in the Endpoint information registered (e.g., twoleafs announcing the same endpoint, duplicate subnets, etc.), amongother such checks.

Tenant Routing Checks

Assurance Appliance 300 can validate that BDs, VRFs, subnets (bothinternal and external), VLANs, contracts, filters, applications, EPGs,etc., are correctly programmed.

Infrastructure Routing

Assurance Appliance 300 can validate that infrastructure routing (e.g.,IS-IS protocol) has no convergence issues leading to black holes, loops,flaps, and other problems.

MP-BGP Route Reflection Checks

The network fabric (e.g., Fabric 120) can interface with other externalnetworks and provide connectivity to them via one or more protocols,such as Border Gateway Protocol (BGP), Open Shortest Path First (OSPF),etc. The learned routes are advertised within the network fabric via,for example, MP-BGP. These checks can ensure that a route reflectionservice via, for example, MP-BGP (e.g., from Border Leaf) does not havehealth issues.

Logical Lint and Real-Time Change Analysis

Assurance Appliance 300 can validate rules in the specification of thenetwork (e.g., L_Model 270A) are complete and do not haveinconsistencies or other problems. MOs in the MIM 200 can be checked byAssurance Appliance 300 through syntactic and semantic checks performedon L_Model 270A and/or the associated configurations of the MOs in MIM200. Assurance Appliance 300 can also verify that unnecessary, stale,unused or redundant configurations, such as contracts, are removed.

FIG. 3B illustrates an architectural diagram of an example system 350for network assurance. In some cases, system 350 can correspond to theDAG of Operators 310 previously discussed with respect to FIG. 3A Inthis example, Topology Explorer 312 communicates with Controllers 116(e.g., APIC controllers) in order to discover or otherwise construct acomprehensive topological view of Fabric 120 (e.g., Spines 102, Leafs104, Controllers 116, Endpoints 122, and any other components as well astheir interconnections). While various architectural components arerepresented in a singular, boxed fashion, it is understood that a givenarchitectural component, such as Topology Explorer 312, can correspondto one or more individual Operators 310 and may include one or morenodes or endpoints, such as one or more servers, VMs, containers,applications, service functions (e.g., functions in a service chain orvirtualized network function), etc.

Topology Explorer 312 is configured to discover nodes in Fabric 120,such as Controllers 116, Leafs 104, Spines 102, etc. Topology Explorer312 can additionally detect a majority election performed amongstControllers 116, and determine whether a quorum exists amongstControllers 116. If no quorum or majority exists, Topology Explorer 312can trigger an event and alert a user that a configuration or othererror exists amongst Controllers 116 that is preventing a quorum ormajority from being reached. Topology Explorer 312 can detect Leafs 104and Spines 102 that are part of Fabric 120 and publish theircorresponding out-of-band management network addresses (e.g., IPaddresses) to downstream services. This can be part of the topologicalview that is published to the downstream services at the conclusion ofTopology Explorer's 312 discovery epoch (e.g., 5 minutes, or some otherspecified interval).

Unified Collector 314 can receive the topological view from TopologyExplorer 312 and use the topology information to collect information fornetwork assurance from Fabric 120. Such information can include L_Model270A and/or LR_Model 270B from Controllers 116, switch softwareconfigurations (e.g., Ci_Model 274) from Leafs 104 and/or Spines 102,hardware configurations (e.g., Hi_Model 276) from Leafs 104 and/orSpines 102, etc. Unified Collector 314 can collect Ci_Model 274 andHi_Model 276 from individual fabric members (e.g., Leafs 104 and Spines102).

Unified Collector 314 can poll the devices that Topology Explorer 312discovers in order to collect data from Fabric 120 (e.g., from theconstituent members of the fabric). Unified Collector 314 can collectthe data using interfaces exposed by Controller 116 and/or switchsoftware (e.g., switch OS), including, for example, a RepresentationState Transfer (REST) Interface and a Secure Shell (SSH) Interface.

In some cases, Unified Collector 314 collects L_Model 270A, LR_Model270B, and/or Ci_Model 274 via a REST API, and the hardware information(e.g., configurations, tables, fabric card information, rules, routes,etc.) via SSH using utilities provided by the switch software, such asvirtual shell (VSH or VSHELL) for accessing the switch command-lineinterface (CLI) or VSH_LC shell for accessing runtime state of the linecard.

Unified Collector 314 can poll other information from Controllers 116,including: topology information, tenant forwarding/routing information,tenant security policies, contracts, interface policies, physical domainor VMM domain information, OOB (out-of-band) management IP's of nodes inthe fabric, etc.

Unified Collector 314 can also poll other information from Leafs 104 andSpines 102, such as: Ci Models 274 for VLANs, BDs, security policies,Link Layer Discovery Protocol (LLDP) connectivity information of Leafs104 and/or Spines 102, endpoint information from EPM/COOP, fabric cardinformation from Spines 102, routing information base (RIB) tables,forwarding information base (FIB) tables from Leafs 104 and/or Spines102, security group hardware tables (e.g., TCAM tables) from switches,etc.

Assurance Appliance 300 can run one or more instances of UnifiedCollector 314. For example, Assurance Appliance 300 can run one, two,three, or more instances of Unified Collector 314. The task of datacollecting for each node in the topology (e.g., Fabric 120 includingSpines 102, Leafs 104, Controllers 116, etc.) can be sharded or loadbalanced, to a unique instance of Unified Collector 314. Data collectionacross the nodes can thus be performed in parallel by one or moreinstances of Unified Collector 314. Within a given node, commands anddata collection can be executed serially. Assurance Appliance 300 cancontrol the number of threads used by each instance of Unified Collector314 to poll data from Fabric 120.

Data collected by Unified Collector 314 can be compressed and sent todownstream services. In some examples, Unified Collector 314 can collectdata in an online fashion or real-time fashion, and send the datadownstream, as it is collected, for further analysis. In some examples,Unified Collector 314 can collect data in an offline fashion, andcompile the data for later analysis or transmission.

Assurance Appliance 300 can contact Controllers 116, Spines 102, Leafs104, and other nodes to collect various types of data. In somescenarios, Assurance Appliance 300 may experience a failure (e.g.,connectivity problem, hardware or software error, etc.) that prevents itfrom being able to collect data for a period of time. AssuranceAppliance 300 can handle such failures seamlessly, and generate eventsbased on such failures.

Switch Logical Policy Generator 316 can receive L_Model 270A and/orLR_Model 270B from Unified Collector 314 and calculate Li_Model 272 foreach network device i (e.g., switch i) in Fabric 120. For example,Switch Logical Policy Generator 316 can receive L_Model 270A and/orLR_Model 270B and generate Li_Model 272 by projecting a logical modelfor each individual node i (e.g., Spines 102 and/or Leafs 104) in Fabric120. Switch Logical Policy Generator 316 can generate Li_Model 272 foreach switch in Fabric 120, thus creating a switch logical model based onL_Model 270A for each switch.

Switch Logical Configuration Generator 316 can also perform changeanalysis and generate lint events or records for problems discovered inL_Model 270A and/or LR_Model 270B. The lint events or records can beused to generate alerts for a user or network operator.

Policy Operator 318 can receive Ci_Model 274 and Hi_Model 276 for eachswitch from Unified Collector 314, and Li_Model 272 for each switch fromSwitch Logical Policy Generator 316, and perform assurance checks andanalysis (e.g., security adherence checks, TCAM utilization analysis,etc.) based on Ci_Model 274, Hi_Model 276, and Li_Model 272. PolicyOperator 318 can perform assurance checks on a switch-by-switch basis bycomparing one or more of the models.

Returning to Unified Collector 314, Unified Collector 314 can also sendL_Model 270A and/or LR_Model 270B to Routing Policy Parser 320, andCi_Model 274 and Hi_Model 276 to Routing Parser 326.

Routing Policy Parser 320 can receive L_Model 270A and/or LR_Model 270Band parse the model(s) for information that may be relevant todownstream operators, such as Endpoint Checker 322 and Tenant RoutingChecker 324. Similarly, Routing Parser 326 can receive Ci_Model 274 andHi_Model 276 and parse each model for information for downstreamoperators, Endpoint Checker 322 and Tenant Routing Checker 324.

After Ci_Model 274, Hi_Model 276, L_Model 270A and/or LR_Model 270B areparsed, Routing Policy Parser 320 and/or Routing Parser 326 can sendcleaned-up protocol buffers (Proto Buffs) to the downstream operators,Endpoint Checker 322 and Tenant Routing Checker 324. Endpoint Checker322 can then generate events related to Endpoint violations, such asduplicate IPs, APIPA, etc., and Tenant Routing Checker 324 can generateevents related to the deployment of BDs, VRFs, subnets, routing tableprefixes, etc.

FIG. 3C illustrates a schematic diagram of an example system for staticpolicy analysis in a network (e.g., Network Environment 100). StaticPolicy Analyzer 360 can perform assurance checks to detect configurationviolations, logical lint events, contradictory or conflicting policies,unused contracts, incomplete configurations, etc. Static Policy Analyzer360 can check the specification of the user's intent or intents inL_Model 270A to determine if any configurations in Controllers 116 areinconsistent with the specification of the user's intent or intents.

Static Policy Analyzer 360 can include one or more of the Operators 310executed or hosted in Assurance Appliance 300. However, in otherconfigurations, Static Policy Analyzer 360 can run one or more operatorsor engines that are separate from Operators 310 and/or AssuranceAppliance 300. For example, Static Policy Analyzer 360 can be a VM, acluster of VMs, or a collection of endpoints in a service functionchain.

Static Policy Analyzer 360 can receive as input L_Model 270A fromLogical Model Collection Process 366 and Rules 368 defined for eachfeature (e.g., object) in L_Model 270A. Rules 368 can be based onobjects, relationships, definitions, configurations, and any otherfeatures in MIM 200. Rules 368 can specify conditions, relationships,parameters, and/or any other information for identifying configurationviolations or issues.

Moreover, Rules 368 can include information for identifying syntacticviolations or issues. For example, Rules 368 can include one or morerules for performing syntactic checks. Syntactic checks can verify thatthe configuration of L_Model 270A is complete, and can help identifyconfigurations or rules that are not being used. Syntactic checks canalso verify that the configurations in the hierarchical MIM 200 arecomplete (have been defined) and identify any configurations that aredefined but not used. To illustrate, Rules 368 can specify that everytenant in L_Model 270A should have a context configured; every contractin L_Model 270A should specify a provider EPG and a consumer EPG; everycontract in L_Model 270A should specify a subject, filter, and/or port;etc.

Rules 368 can also include rules for performing semantic checks andidentifying semantic violations or issues. Semantic checks can checkconflicting rules or configurations. For example, Rule1 and Rule2 canhave aliasing issues, Rule1 can be more specific than Rule2 and therebycreate conflicts/issues, etc. Rules 368 can define conditions which mayresult in aliased rules, conflicting rules, etc. To illustrate, Rules368 can specify that an allow policy for a specific communicationbetween two objects can conflict with a deny policy for the samecommunication between two objects if the allow policy has a higherpriority than the deny policy, or a rule for an object renders anotherrule unnecessary.

Static Policy Analyzer 360 can apply Rules 368 to L_Model 270A to checkconfigurations in L_Model 270A and output Configuration Violation Events370 (e.g., alerts, logs, notifications, etc.) based on any issuesdetected. Configuration Violation Events 370 can include semantic orsemantic problems, such as incomplete configurations, conflictingconfigurations, aliased rules, unused configurations, errors, policyviolations, misconfigured objects, incomplete configurations, incorrectcontract scopes, improper object relationships, etc.

In some cases, Static Policy Analyzer 360 can iteratively traverse eachnode in a tree generated based on L_Model 270A and/or MIM 200, and applyRules 368 at each node in the tree to determine if any nodes yield aviolation (e.g., incomplete configuration, improper configuration,unused configuration, etc.). Static Policy Analyzer 360 can outputConfiguration Violation Events 370 when it detects any violations.

FIG. 4 illustrates a flowchart for an example network assurance method.The methods illustrated herein are provided by way of example, as thereare a variety of ways to carry out the various methods disclosed.Additionally, while the example methods are illustrated with aparticular order of blocks, operations, or steps, those of ordinaryskill in the art will appreciate that the blocks, operations, or stepscan be executed in any order and can include fewer or more blocks,operations, or steps than illustrated.

Each block, operation, or step shown in FIG. 4 represents one or moresteps, processes, methods, or routines in the methods. For the sake ofclarity and explanation purposes, the FIG. 4 is described with referenceto Assurance Appliance 300, Models 270A-B, 272, 274, 276, and NetworkEnvironment 100, as shown in FIGS. 1A-B, 2D, and 3A.

At step 400, Assurance Appliance 300 can collect data and obtain modelsassociated with Network Environment 100. The models can include Models270A-B, 272, 274, 276. The data can include fabric data (e.g., topology,switch, interface policies, application policies, EPGs, etc.), networkconfigurations (e.g., BDs, VRFs, L2 Outs, L3 Outs, protocolconfigurations, etc.), security configurations (e.g., contracts,filters, etc.), service chaining configurations, routing configurations,and so forth. Other information collected or obtained can include, forexample, network data (e.g., RIB/FIB, VLAN, MAC, ISIS, DB, BGP, OSPF,ARP, VPC, LLDP, MTU, QoS, etc.), rules and tables (e.g., TCAM rules,ECMP tables, etc.), endpoint dynamics (e.g., EPM, COOP EP DB, etc.),statistics (e.g., TCAM rule hits, interface counters, bandwidth, etc.).

At step 402, Assurance Appliance 300 can analyze and model the receiveddata and models. For example, Assurance Appliance 300 can perform formalmodeling and analysis, which can involve determining equivalency betweenmodels, including configurations, policies, etc.

At step 404, Assurance Appliance 300 can generate one or more smartevents. Assurance Appliance 300 can generate smart events using deepobject hierarchy for detailed analysis, such as Tenants, switches, VRFs,rules, filters, routes, prefixes, ports, contracts, subjects, etc.

At step 406, Assurance Appliance 300 can visualize the smart events,analysis, and/or models. Assurance Appliance 300 can display problemsand alerts for analysis and debugging, in a user-friendly GUI.

According to various aspects of the subject technology, networkassurance activities for endpoints in a network may involve collectinginformation from various sources in the network and performing one ormore endpoint checks or network assurance checks. The information may becollected from one or more network controllers (e.g., an APICcontroller), network administrators, services, data stores, endpoints,leaf nodes, and/or spine nodes. The information collected may includedata from the concrete model, logical model, or hardware model. Forexample, a network assurance appliance may query a network controller toobtain topology information for a network, query concrete modelinformation from one or more nodes in the network, and/or collectlogical model information from the controller.

In some cases, an endpoint may connect to a leaf node and the leaf nodewill learn information about the endpoint. The learned information mayinclude, for example, an interface identifier on which the endpointconnects to the leaf node, an endpoint group that the endpoint belongsto, VLAN information, encapsulation information, etc. The leaf node maypublicize the route to the newly connected endpoint to inform the othernodes in the network that communication to the new endpoint is throughthat leaf node. This endpoint may be considered a learned endpoint. Inother situations, an endpoint may be a static endpoint that, instead ofbeing learned, is specified by a network controller based on a logicalmodel.

The endpoint checking functionality of the network assurance appliancevalidates endpoint information. In some applications, the networkassurance appliance collects information about endpoints in the network,sorts that information, and validates that the information about theendpoints is consistent across nodes (e.g., leaf nodes and spine nodes).For example, data from the local search (LST) table that includes layer2 and/or layer 3 information may be collected from leaf nodes andcorresponding information may be collected from spine nodes. Theinformation may be combined and compared to identify inconsistencies ormismatches.

If inconsistencies or mismatches are found, the network assuranceappliance may generate an event, notify a network administrator of theevent, log the event, and/or attempt to resolve the issue. According toother aspects, information from other routing tables (LPM table, GSTtable, etc.) maintained by the nodes may also be explored to identifyinconsistencies or mismatches. There may be various causes forinconsistencies and mismatches in endpoint information across thenetwork. For example, problems may be caused by a spine or leafmalfunction or reboot, a node dropping off and coming back on, a problemwith various communication including controller to leaf communication orroute learning protocols.

FIG. 5 illustrates an example network environment, in accordance withvarious aspects of the subject technology. In this example, networkenvironment 500 includes endpoints 522 connected to leafs 504 in fabric520. Fabric 520 can include spines 502 (e.g., spine routers or switches)and leafs 504 (e.g., leaf routers or switches) which can beinterconnected for routing or switching traffic in the fabric 520.Spines 502 can interconnect leafs 504 in the fabric 520, and leafs 504can connect the fabric 520 to an overlay or logical portion of thenetwork environment 500, which can include application services,servers, virtual machines, containers, endpoints, etc. Thus, networkconnectivity in the fabric 520 can flow from spines 502 to leafs 504,and vice versa. The interconnections between leafs 504 and spines 502can be redundant (e.g., multiple interconnections) to avoid a failure inrouting. In some embodiments, leafs 504 and spines 502 can be fullyconnected, such that any given leaf is connected to each of the spines502, and any given spine is connected to each of the leafs 504.

As suggested above, the network assurance appliance may collectinformation about the endpoints from spine nodes 502. The informationcollected from the spines 502 in the fabric 520 may be combined andstored. A simplified representation of the combined data collected bythe network assurance appliance is illustrated in the table below:

TABLE 1 EP1 EP2 EP3 EP4 Spine1 Spine1 Spine1 Spine1 Spine2 Spine2 Spine2Spine2

The combined data indicates that endpoint 1 (EP1) is reachable by spine1 and spine 2, endpoint 2 (EP2) is reachable by spine 1 and spine 2,endpoint 3 (EP3) is reachable by spine 1 and spine 2, endpoint 4 (EP4)is reachable by spine 1 and spine 2. Each spine in the fabric 520 shouldhave information about all endpoints 522 in the fabric since a leaf mayroute traffic towards any spine.

The network assurance appliance may also collect information about theendpoints in the fabric 520 from the leafs 504. The informationcollected from the leafs 504 in the fabric 520 may be combined andstored. A simplified representation of the combined data collected fromthe leafs 504 may be:

TABLE 2 EP1 EP2 EP3 EP4 Leaf1 Leaf1 Leaf2 Leaf2

The combined data collected from the leafs 504 indicates that endpoint 1(EP1) is reachable via leaf 1, endpoint 2 (EP2) is reachable via leaf 1,endpoint 3 (EP3) is reachable via leaf 2, and endpoint 4 (EP4) isreachable via leaf 2. In various aspects of the subject technology, thenetwork assurance appliance collects additional information from thespines 502 and leafs 504 that is not included in the simplifiedrepresentations above. This additional information may include, forexample, tunnel endpoint (TEP) addresses, IP addresses, MAC addresses,bridge domain (BD) information, endpoint group (EPG) information, L3outinformation, VRF information, various endpoint flags/properties, orother information associated with the endpoints 522.

The routing information collected a leaf node may be considered, in somesituations, to be a source of truth for endpoint information forendpoints that are connected to the leaf node. The endpoint informationmay be compared with endpoint information collected from the spine nodes502 in the fabric 520. The endpoint information in the spine nodes 502is typically derived from information publicized by one or more leafnodes 504 in the network and is stored in various routing tables, lookuptables, or other data stores on the spine nodes 502.

Validating Endpoint Configurations Between Nodes

FIG. 6 illustrates an example method embodiment for validating anendpoint configuration between nodes, in accordance with various aspectsof the subject technology. At operation 602, the network assuranceappliance may retrieve endpoint information from one or more spine nodesin a network fabric. The endpoint information includes routing and othernetwork information about endpoints in the network. The informationretrieved from the one or more spine nodes may be combined into a singleset of data for the spine nodes. At operation 604, the network assuranceappliance may retrieve endpoint information from one or more leaf nodesin the network fabric. This information may similarly be combined into aset of data for the leaf nodes.

At operation 606, the network assurance appliance may compare theendpoint information from the one or more leaf nodes with the endpointinformation from the one or more spine nodes and, at operation 608,determine whether there is an inconsistency based on the comparison. Aninconsistency may indicate erroneous endpoint information stored on oneof the nodes in the fabric and, in response, the network assuranceappliance may generate an event, notify a network administrator of theevent, log the event, and/or attempt to resolve the issue.

Although the method in FIG. 6 discusses comparing combined endpointinformation from leaf nodes with combined endpoint information fromspine nodes, other comparisons may also be performed by the networkassurance appliance including, for example, comparisons of endpointinformation between spine nodes, comparisons of endpoint informationbetween leaf nodes, and/or comparisons of endpoint information betweenfrom single nodes.

Check that all Detected Endpoints are Known to all Spines

The network assurance appliance may use the method of FIG. 6 to checkfor various inconsistencies. For example, a check to make sure that allendpoints are known to all spines in the fabric may be performed. Morespecifically, the network assurance appliance checks whether allendpoints detected by the leaf nodes are also known to each spine in thefabric. As discussed above, the endpoint information may be retrievedfrom the leaf nodes in the fabric and specify the endpoints detected bythe leaf nodes in the network.

A simplified representation of the endpoint information collected fromthe leaf nodes is illustrated in the table below:

TABLE 3 EP1 EP2 EP3 EP4 Leaf1 Leaf1 Leaf2 Leaf2

The endpoint information from the leaf nodes indicates that endpointsEP1 and EP2 are connected to leaf node 1 and that endpoints EP3 and EP4are connected to leaf node 2. The leaf nodes enable the variousendpoints EP1-EP4 connected to them to transmit data through the networkfabric and allow other endpoints to reach the connected endpoint.

For illustrative purposes, the endpoint information collected from thespine nodes in one scenario may be illustrated in the table below:

TABLE 4 EP1 EP2 EP3 EP4 Spine1 Spine1 Spine1 Spine1 Spine2 Spine2 Spine2Spine2

The network assurance appliance may compare the endpoint informationcollected from the leaf nodes with the endpoint information collectedfrom the spine nodes and determine whether there is an inconsistencybased on the comparison. More specifically, the network assuranceappliance may compare the information in Table 3 and Table 4 above anddetermine that there is no inconsistency because all endpoints detectedby the leaf nodes are known to each and every spine node in the fabric.

In another illustrative scenario, the endpoint information collectedfrom the spine nodes can be represented by Table 5 below:

The network assurance appliance may compare the information in Table 3and Table 5 above and determine that there is an inconsistency becauseEP4, which has been detected by leaf node 2 (see Table 3), is not knownto either spine node according to the information in Table 5.

Similarly, in another illustrative scenario, the endpoint informationcollected from the spine nodes can be represented by Table 6 below:

Again, network assurance appliance may compare the information in Table3 and Table 6 above and determine that there is an inconsistency becauseEP4, which has been detected by leaf node 2, is not known to spine node2 (although it is known to spine node 1). If any such inconsistency isdetected, the network assurance appliance may generate an event, notifya network administrator of the event, log the event, and/or attempt toresolve the issue (e.g., restart a malfunctioning node, etc.).

Check for Flag and IP Inconsistencies

The endpoint information retrieved by the network assurance appliancemay include additional information such as MAC addresses, TEP addresses,IP addresses, subnet information, bridge domain (BD) information,endpoint group (EPG) information, L3out information, VRF information,various endpoint flags, or other information associated with theendpoints. The various endpoint flags include, for example, is_hostflags, is_router flags, is_vpc flags, scope_ID flags, PC_tag flags, andother flags used to specify information for endpoints on a network.These flags may depend on the implementation of the network.

In addition to or alternatively, the network assurance appliance mayalso check whether the flags in the endpoint information retrieved fromthe spines and the flags in the endpoint information retrieved from theleafs are consistent. If any such inconsistency is detected, the networkassurance appliance may generate an event, notify a networkadministrator of the event, log the event, and/or attempt to resolve theissue (e.g., restart a malfunctioning node, execute an endpoint learningprocess, etc.).

In addition to or alternatively, the network assurance appliance mayalso check whether the IP address information in the endpointinformation retrieved from the spines and the IP address information inthe endpoint information retrieved from the leafs are consistent. Forexample, endpoint information maintained by a leaf node or a spine nodemay include a bridge domain ID, a MAC address, and one or more IPaddresses. For endpoints that include one or more virtual machines,multiple IP addresses may be needed. The network assurance appliancevalidates the number and value of the various IP addresses for anendpoint detected by a leaf node and the number and value of the variousIP addresses for the endpoint from the endpoint information retrievedfrom the spine nodes. If an inconsistency is detected, the networkassurance appliance may generate an event, notify a networkadministrator of the event, log the event, and/or attempt to resolve theissue (e.g., restart a malfunctioning node, execute an endpoint learningprocess, etc.).

Check that Each Endpoint Found by the Spine Nodes are Connected to aLeaf

The network assurance appliance may perform a check to determine whethereach endpoint found in the endpoint information from the one or morespine nodes is connected to a leaf node. For example, for each endpointidentified in the endpoint information retrieved from the spine nodes,the network assurance appliance may check to make sure the endpoint isalso in the endpoint information retrieved from the leaf nodes. If theendpoint is not found in the endpoint information from the leaf nodes,there is an inconsistency.

Check that Each Endpoint is Only Connected to One Leaf (e.g., EndpointConsistency Check)

The network assurance appliance may also perform a check to determinewhether each endpoint is only connected to one leaf node. In somenetwork configurations, endpoints may only be connected to one leaf nodeunless they are configured otherwise (e.g., VPC endpoints or pervasiveendpoints). For the endpoints that are to be connected to one leaf node,checks are performed that only one leaf node detects each endpoint.

According to some aspects of the subject technology, the networkassurance appliance may retrieve endpoint information from the leafnodes in the network and determine whether an endpoint is detected bymore than one leaf node. If more than one leaf node detects an endpoint,and the endpoint is not a specialized endpoint configured to connect tomore than one leaf node (e.g., VPC endpoints or pervasive endpoints),the network assurance appliance may determine there is an inconsistency.

Duplicate IP Check

The network assurance appliance may perform a check to determine whetherthere are any duplicate IPs in the network fabric. For example, thenetwork assurance appliance may check to make sure the IP addresses forthe endpoint in the endpoint information retrieved from the nodes areunique and are not identical with another IP address for an endpoint inthe fabric. If a duplicate IP address is found, there is amisconfiguration.

Validating Tunnel Endpoint Addresses in a Network Fabric

Tunnel endpoint (TEP) addresses are used to route traffic through thefabric in ACI networks and other similar networks. Each node may beassigned a physical TEP address and use the TEP addresses of other nodesin the fabric to transmit data internally within the fabric. Forexample, a logical model may be rendered into concrete models forvarious nodes and the concrete models are used to assign TEP addressesto the nodes. Accordingly, each leaf node will have a correspondingphysical TEP (PTEP) address that it has been assigned. The PTEP is an IPaddress that represents the leaf node's VXLAN tunnel endpoint (VTEP).

Each spine node that is configured to communicate with endpoints in thenetwork fabric should know which leaf's PTEP address to use whencommunicating with a particular endpoint. For example, a simplifiedrepresentation of the endpoint data collected from the spine nodes 502of FIG. 5 may be:

TABLE 7 EP1 EP2 EP3 EP4 Spine1 - Spine1 - Spine1 - Spine1 - TEP_L1TEP_L1 TEP_L2 TEP_L2 Spine2 - Spine2 - Spine2 - Spine2 - TEP_L1 TEP_L1TEP_L2 TEP_L2

The endpoint data from the spines indicates that endpoints 1 and 2 (EP1and EP2) are reachable by spine 1 and by spine 2 through the TEP address“TEP_L1.” The TEP_L1 address should be the PTEP address for leaf 1,which “learned” or is connected to EP1 and EP2. Similarly, endpoints 3and 4 (EP3 and EP4) are reachable by spine 1 and by spine 2 through theTEP address “TEP_L2.” The TEP_L2 address should be the PTEP address forleaf 2 because EP3 and EP4 are connected to the network fabric throughleaf 2. In some cases, however, the TEP address for an endpoint may besomething other than the PTEP address for the leaf node that to whichthe endpoint is connected. For example, when an endpoint is connected tothe network fabric through a virtual port channel (VPC), the spine noderoutes traffic to the endpoint through a virtual IP (VIP) address. ThisVIP address would be stored as the TEP address for the VPC endpoint.

There may be situations, however, where the TEP addresses from thedifferent spines may be different from one another and situations whereone or more spines has an incorrect TEP address for one or more of theendpoints. According to various aspects of the subject technology, thenetwork assurance appliance is configured to determine whether the spinenodes have the correct TEP address for a leaf node where an endpoint islearned on or connected to. The TEP address may be a physical tunnelendpoint (PTEP) address for “single node” endpoints (e.g., endpointsthat are connected to only the single leaf node) or a VIP address forVPC endpoints. Various checks may be performed to ensure that the spinenodes have correct TEP addresses for endpoints.

For example, the network assurance appliance may obtain endpointinformation from one or more spine nodes. The endpoint information, suchas is illustrated in table 7 above, includes TEP addresses for eachendpoint that the spine(s) knows of. The network assurance appliance mayquery a leaf node for endpoint information. The endpoint informationfrom the queried leaf node may include endpoint identifiers for one ormore endpoints that the leaf node has learned or that the leaf nodeconnects to the network fabric. For each endpoint identified by thequeried leaf node, the network assurance can check each spine's endpointinformation to make sure that the spine's endpoint information has thecorrect TEP address for the identified endpoint. The correct TEP addressmay be a PTEP for a leaf node that the endpoint is connected to or a VIPaddress for the endpoint in the endpoint is a VPC node. If aninconsistency is detected, the network assurance appliance may generatean event, notify a network administrator of the event, log the event,and/or attempt to resolve the issue.

FIG. 7 illustrates an example method embodiment for validating anendpoint configuration between nodes, in accordance with various aspectsof the subject technology. At operation 702 the network assuranceappliance may retrieve endpoint information for an endpoint connected toa leaf node in the network fabric. For example, the network assuranceappliance may query a leaf node in the network for endpoint informationfor all endpoints that are connected to the leaf node. The endpointinformation may include various IP addresses, endpoint identifiers, flaginformation indicating an endpoint type (e.g., pervasive endpoint,single node endpoint, VPC endpoint, etc.).

At operation 704, an actual tunnel endpoint address for the endpoint maybe retrieved from one or more spine nodes in the network. The actualtunnel endpoint address may be stored by the spine nodes and used toroute network traffic to the endpoint.

At operation 706, the network assurance appliance may identify areference tunnel endpoint address for the endpoint. According to someaspects of the subject technology, the reference tunnel endpoint addressfor an endpoint may depend on the type of endpoint. For example, thereference tunnel endpoint address for a single node endpoint is the PTEPaddress for the leaf node that the single node endpoint is connected to.The reference tunnel endpoint address for a VPC endpoint is the VIPaddress for the VPC that the endpoint uses to connect to the networkfabric. The reference tunnel endpoint address for a pervasive endpointmay be the PTEP address for any of the leaf nodes that the pervasiveendpoint is connected to.

The type of endpoint may be determined based on the retrieved endpointinformation. For example, the endpoint information may include flagsthat indicate which type of endpoint that an endpoint is. In someimplementations, the type of endpoint may be determined based on logicalor concrete model information retrieved from a network controller.

At operation 708, the network assurance appliance determines whetherthere is an inconsistency based on a comparison of the actual tunnelendpoint address with the reference tunnel endpoint address. If theactual TEP address and the reference TEP do not match, an inconsistencymay be declared.

Static Endpoint Validation

As noted above, some endpoints are learned. When the endpointestablishes a connection to a leaf node, the leaf node publicizes theroute to the endpoint to other nodes in the network. However, endpointsmay also be static in that, instead of being learned, the endpoint isdefined by a network controller based on a logical model. This may beused, for example, to configure silent hosts in a network.

The network assurance appliance may perform various checks to validatestatic endpoint information in the fabric. For example, as discussedabove, the network assurance appliance may obtain endpoint informationfrom leaf nodes and spine nodes in the system and compare thisinformation to detect inconsistencies between nodes. The endpointinformation includes flags such as a flag indicating whether an endpointis a static endpoint (e.g., an “is static” flag). Accordingly, thestatic endpoint flag included in the endpoint information may becompared to determine whether there are inconsistencies with the flag.

The endpoint information also includes endpoint group identifierinformation for the endpoint group that an endpoint belongs to,interface/port identifiers for the interface/port that the endpoint isconnected to, encap VLAN information for the endpoint, etc. The networkassurance appliance may compare the above information from leaf nodesand spine nodes to detect inconsistencies.

Additionally, or alternatively, the network assurance appliance maycheck that any static endpoint defined by the logical model is detectedby the nodes (e.g., leafs or spines) in the fabric and specified by thenodes as a static endpoint. The network assurance appliance may alsocheck whether an endpoint identified by one or more of the nodes in thefabric as a static endpoint has a corresponding static endpoint definedby the logical model.

FIG. 8 illustrates an example method embodiment for static endpointvalidation, in accordance with various aspects of the subjecttechnology. At operation 802, the network assurance appliance may querya network controller to identify a configured static endpoint in alogical model of a network. At operation 804, endpoint information isretrieved from one or more nodes in the network. The endpointinformation may be obtained from a leaf node, a spine node, or acombinations of nodes. At operation 806, the network assurance appliancedetermines whether the endpoint information includes a connectedendpoint that corresponds to the configured static endpoint in thelogical model.

For example, the logical model may specify that an endpoint is a staticendpoint and include various information for the static endpoint. Theinformation may include an endpoint identifier, a leaf node that thestatic endpoint is to connect to, a port that the static endpoint is touse to connect to the leaf node, flag information, or any otherinformation associated with the static endpoint. The information aboutthe static endpoint may vary and/or depend on a particularimplementation. The endpoint information may correspond with theconfigured static endpoint in the logical model if some or all of theinformation in the configured static endpoint matches the endpointinformation from the one or more nodes.

If there is no corresponding connected endpoint at operation 808, thereis an inconsistency. If there is a corresponding connected endpoint, atoperation 810 the static flag for the connected endpoint may be checkedto see if it is set. If the static flag is not set, there is aninconsistency at operation 812. If the static flag is set, the staticendpoint is validated for this check at operation 814. If aninconsistency is detected at operations 808 or 812, the networkassurance appliance may generate an event, notify a networkadministrator of the event, log the event, and/or attempt to resolve theissue.

According to various aspects, the network assurance appliance may alsodetect a static endpoint in the network and determine whether thelogical model has a corresponding static endpoint defined. For example,the network assurance appliance may retrieve endpoint information fromone or more nodes in the network, identify a connected static endpointin the endpoint information based on a static flag for the connectedstatic endpoint being set, and query a network controller to determinewhether there is a configured static endpoint in the logical model ofthe network. If there is no configured static endpoint that correspondsto the connected static endpoint, there is an inconsistency. If aninconsistency is detected, the network assurance appliance may generatean event, notify a network administrator of the event, log the event,and/or attempt to resolve the issue.

Endpoint IP BD Subnet Validation

A bridge domain (BD) represents a Layer 2 forwarding construct within asoftware-defined network fabric. The bridge domain may be linked to aVRF (e.g., a context or private network) and associated with one or moreIP subnets (e.g., ranges of IP addresses). For example, the BD maydefine a unique Layer 2 MAC address space and a Layer 2 flood domain ifsuch flooding is enabled. While a VRF defines a unique IP address space,that address space can consist of multiple subnets. Those subnets aredefined in one or more bridge domains that reference the correspondingVRF.

Bridge domains can span multiple nodes (e.g., switches). According tosome implementations, a bridge domain can contain multiple subnets. Ifthe bridge domain (BD) limitIPLearnToSubnets flag/property is set toyes, endpoint learning will occur in the bridge domain if the IP addressis within any of the configured subnets for the bridge domain or withinan EPG subnet when the EPG is a shared service provider. Subnets canspan multiple EPGs; one or more EPGs can be associated with one bridgedomain.

A bridge domain may be defined and implemented for a tenant to helporganize network traffic in a data center or fabric. For example,certain endpoint groups (EPGs) may have different functions or supportdifferent applications (e.g., web servers, database servers, applicationservers, etc.). Each EPG may be associated with a particular bridgedomain (BD). Each bridge domain may be associated with one or more IPsubnets.

According to various aspects of the subject technology, the networkassurance appliance may be configured to check endpoints in a bridgedomain to see whether the one or more IP addresses associated with eachendpoint falls within one of the subnets associated with the bridgedomain.

FIG. 9 illustrates an example method embodiment for static endpointvalidation, in accordance with various aspects of the subjecttechnology. Bridge domains may be specified in a logical model as beingassociated with a bridge domain identifier, one or more subnets, andvarious flags or properties. One such flag may include a “Limit IPLearning to Subnet” flag which, if set, limits leaf node learning to IPsfor the bridge domain subnet(s). This information may be stored at thenetwork controller in the logical model.

The network assurance appliance may query the network controller for thelogical model or the bridge domain specification in the logical mode.Also as described above, endpoint information for the various endpointsmay be collected from one or more nodes in the fabric. This endpointinformation includes the various IP addresses each endpoint isassociated with. Below is a simplified representation of the informationstored in the bridge domain specification for Bridge Domain A (see Table8) as well as a simplified representation of endpoint information forEP1 (see Table 9):

TABLE 8 Bridge Domain A Subnet1 Subnet2 Subnet3Limit_IP_Learning_to_Subnet flag [x]

TABLE 9 EP1 IP1 IP2 IP9

The simplified representation of the bridge domain specificationindicates that bridge domain A is associated with subnets 1, 2, and 3.The simplified representation of endpoint information for EP1 indicatesthat EP1 is associated with the IP1, IP2, and IP9 IP addresses.

At operation 902, the network assurance appliance may identify one ormore endpoints in a bridge domain. The network assurance appliance mayretrieve, for each endpoint, endpoint information from the one or morenodes in the fabric. At operation 904, at least one IP addressassociated with the endpoint is retrieved. The network assuranceappliance may determine whether each IP address is within one of thesubnets associated with the bridge domain at operation 906. If we usethe information provided in tables 8 and 9 above as an example, thenetwork assurance appliance will determine whether each of IP1, IP2, andIP9 are within one of subnet1, subnet2, or subnet 3.

If each IP address is within one of the subnets, there is noinconsistency. If not, however, the network assurance appliance maydetermine that there is an inconsistency at operation 908 and thenetwork assurance appliance may generate an event, notify a networkadministrator of the event, log the event, and/or attempt to resolve theissue.

According to some implementations, the network assurance appliance mayalso determine whether the flag for limiting IP learning to subnets isset of the bridge domain. In some cases, this may determine whether theoperations 902-908 are performed at all. In some cases, whether the flagis set may help determine the rating of an event or notification (e.g.,an important, serious, critical event or notification versus a lowertiered event or notification).

According to various aspects of the subject technology, the networkassurance appliance may perform various checks and generate variousevents based on the performed checks. For example, if an inconsistencyor error is found based on a performed check, the network assuranceappliance may generate an event and store the event in an event log. If,based on a check, certain network configurations are operating correctlyor no error is found, the network assurance appliance may also generatean event indicating that no error is found with respect to the performedcheck and store the event in an event log.

The generated events may be provided to a network administrator toinform the network administrator about the status of the network fabricand/or suggest potential actions to take. For example, the events may beused to generate a notification, a report, a user interface, or othermedium to inform the network administrator.

FIGS. 10A-10F illustrate example user interfaces, in accordance withvarious aspects of the subject technology. The network assuranceappliance may provide various user interfaces or enable various userinterfaces for network administrators to view the status of the networkfabric and, in particular, the endpoint configuration in the networkfabric.

For example, FIG. 10A illustrates an example interface where a networkadministrator may select a network fabric for viewing using interfaceelement 1002 and a particular time period at using interface element1004. In response to the selections, the network assurance appliance mayprovide information relating to endpoint and fabric configuration acrossthe selected network fabric at a particular time period. For example,the network assurance appliance may perform various checks periodically,generate events based on the checks, and store the events in event logs.This information may be summarized and categorized by, for example,severity of the event(s), health of the endpoints (EPs), or type ofendpoint events as shown in FIG. 10A. Furthermore, the information maybe grouped based on the time period in which they can be attributed toso that the network administrator can identify trends and changes in thenetwork fabric over time.

According to various aspects of the subject technology, the networkassurance appliance may compute a score for an endpoint, an endpointgroup, a tenant, an app profile, a VRF, a bridge domain, a tenant, orany other entity in the network fabric based on a number of events, thetype of events generated, the severity of events generated, and/ortrends or patterns in the events over time.

For example, a health score may be calculated for endpoints in thenetwork based on a number of events associated with the endpoint, thetype of events associated with the endpoint, the severity of thoseevents, and/or event trends over time. An endpoint may be categorized ashealthy or unhealthy based on the health score. For example, if thehealth score of an endpoint is above a threshold, it may be consideredhealthy. If the endpoint's health score is below the threshold, it maybe considered unhealthy. The threshold may be based on a set value, anaverage value, or may be a combination of thresholds.

FIG. 10B illustrates an example interface that provides a visualizationof the relationship between a leaf node, a set of endpoints associatedwith the leaf node, and unhealthy endpoints in the set. In particular,the example interface shown in FIG. 10B provides a list of leaf nodes inthe fabric, the total number of endpoints (EPs) connected to each leafnode, and the number of endpoints that are considered unhealthy that areconnected to each leaf node. In other embodiments, the total number ofendpoints and unhealthy endpoints may be provided for an endpoint group,a tenant, an app profile, a VRF, a bridge domain, a tenant, or any otherentity in the network fabric.

FIG. 10C illustrates an example interface that provides a visualizationof the relationship between a leaf node and a number of eventsassociated with the leaf node. The events are grouped based on theseverity of the events. For example, leaf 1 in the “candid2” fabric isassociated with 3 critical events, 2 major events, 0 minor events, 2warnings, and 10 informational events. In other embodiments, other typesof categories based on event severity may be used. Furthermore, in otherembodiments, the number of events based on severity may be provided foran endpoint group, a tenant, an app profile, a VRF, a bridge domain, atenant, or any other entity in the network fabric.

FIGS. 10D and 10E provide additional example interfaces that enable anetwork administrator to interact with the interface and select views ofthe information. For example, FIG. 10D illustrates an example interfacethat provides a visualization of the health of a leaf node. Theinterface may provide a network administrator with a view of the totalnumber of endpoints connected to a leaf node and/or a number ofunhealthy endpoints connected to the leaf node. The interface mayprovide a network administrator with a view of the total number ofevents associated with a leaf node, which may be organized based onseverity or subcategory (e.g., the type of event). Interface element 610enables a network administrator to view unhealthy endpoints, allendpoints, or both. Interface element 612 enables a networkadministrator to view events based on severity or subcategory. The userinterface may be color coded to improve readability. Interface element614 provides a key to illustrate what severity each color corresponds.The network administrator can select a color to view additionalinformation.

As discussed above, the information provided in the user interfaces maybe for leaf nodes, endpoint groups, tenants, app profiles, VRFs, bridgedomains, tenants, or other entity type in the network fabric. Interfaceelement 616 enables a network administrator to select the view based onthe entity type. FIG. 10E illustrates an example interface providinginformation based on endpoint groups. Interface element 620 illustratesa dropdown menu showing possible entity types that may be selected andused to provide information to a network administrator. In interfaceelement 620, an endpoint group (EPG) entity type is selected.Accordingly, interface element 622 displays information organized basedon the endpoint groups in the network fabric (e.g., an App endpointgroup, a Web endpoint group, etc.).

FIG. 10F illustrates an example interface that enables a networkadministrator to view events and select a particular event to view moreinformation on. For example, the interface in FIG. 10F may show allevents during a particular time period or events for a particular entity(e.g., a leaf, an endpoint group, a tenant, an app profile, a VRF, abridge domain, a tenant) during the time period. For example, a networkadministrator may select a particular entity shown in FIGS. 10A-10E toview all events for a time period associated with that entity.

Each row in FIG. 10F may correspond with an event in the event log.Column 630 may indicate the severity of each event, column 632 mayindicate the subcategory or event type for each event, column 634 mayindicate the event name for each event, and 636 may provide an eventdescription for each event. The network administrator may select a rowfor an event to view more information about the event.

The disclosure now turns to FIGS. 11 and 12, which illustrate examplenetwork devices and computing devices, such as switches, routers, loadbalancers, client devices, and so forth.

FIG. 11 illustrates an example network device 1100 suitable forperforming switching, routing, load balancing, and other networkingoperations. Network device 1100 includes a central processing unit (CPU)1104, interfaces 1102, and a bus 1110 (e.g., a PCI bus). When actingunder the control of appropriate software or firmware, the CPU 1104 isresponsible for executing packet management, error detection, and/orrouting functions. The CPU 1104 preferably accomplishes all thesefunctions under the control of software including an operating systemand any appropriate applications software. CPU 1104 may include one ormore processors 1108, such as a processor from the INTEL X86 family ofmicroprocessors. In some cases, processor 1108 can be specially designedhardware for controlling the operations of network device 1100. In somecases, a memory 1106 (e.g., non-volatile RAM, ROM, etc.) also forms partof CPU 1104. However, there are many different ways in which memorycould be coupled to the system.

The interfaces 1102 are typically provided as modular interface cards(sometimes referred to as “line cards”). Generally, they control thesending and receiving of data packets over the network and sometimessupport other peripherals used with the network device 1100. Among theinterfaces that may be provided are Ethernet interfaces, frame relayinterfaces, cable interfaces, DSL interfaces, token ring interfaces, andthe like. In addition, various very high-speed interfaces may beprovided such as fast token ring interfaces, wireless interfaces,Ethernet interfaces, Gigabit Ethernet interfaces, ATM interfaces, HSSIinterfaces, POS interfaces, FDDI interfaces, WIFI interfaces, 3G/4G/5Gcellular interfaces, CAN BUS, LoRA, and the like. Generally, theseinterfaces may include ports appropriate for communication with theappropriate media. In some cases, they may also include an independentprocessor and, in some instances, volatile RAM. The independentprocessors may control such communications intensive tasks as packetswitching, media control, signal processing, crypto processing, andmanagement. By providing separate processors for the communicationsintensive tasks, these interfaces allow the master microprocessor 604 toefficiently perform routing computations, network diagnostics, securityfunctions, etc.

Although the system shown in FIG. 11 is one specific network device ofthe present invention, it is by no means the only network devicearchitecture on which the present invention can be implemented. Forexample, an architecture having a single processor that handlescommunications as well as routing computations, etc., is often used.Further, other types of interfaces and media could also be used with thenetwork device 1100.

Regardless of the network device's configuration, it may employ one ormore memories or memory modules (including memory 1106) configured tostore program instructions for the general-purpose network operationsand mechanisms for roaming, route optimization and routing functionsdescribed herein. The program instructions may control the operation ofan operating system and/or one or more applications, for example. Thememory or memories may also be configured to store tables such asmobility binding, registration, and association tables, etc. Memory 1106could also hold various software containers and virtualized executionenvironments and data.

The network device 1100 can also include an application-specificintegrated circuit (ASIC), which can be configured to perform routingand/or switching operations. The ASIC can communicate with othercomponents in the network device 1100 via the bus 1110, to exchange dataand signals and coordinate various types of operations by the networkdevice 1100, such as routing, switching, and/or data storage operations,for example.

FIG. 12 illustrates a computing system architecture 1200 wherein thecomponents of the system are in electrical communication with each otherusing a connection 1205, such as a bus. Exemplary system 1200 includes aprocessing unit (CPU or processor) 1210 and a system connection 1205that couples various system components including the system memory 1215,such as read only memory (ROM) 1220 and random access memory (RAM) 1225,to the processor 1210. The system 1200 can include a cache of high-speedmemory connected directly with, in close proximity to, or integrated aspart of the processor 1210. The system 1200 can copy data from thememory 1215 and/or the storage device 1230 to the cache 1212 for quickaccess by the processor 1210. In this way, the cache can provide aperformance boost that avoids processor 1210 delays while waiting fordata. These and other modules can control or be configured to controlthe processor 1210 to perform various actions. Other system memory 1215may be available for use as well. The memory 1215 can include multipledifferent types of memory with different performance characteristics.The processor 1210 can include any general purpose processor and ahardware or software service, such as service 1 1232, service 2 1234,and service 3 1236 stored in storage device 1230, configured to controlthe processor 1210 as well as a special-purpose processor where softwareinstructions are incorporated into the actual processor design. Theprocessor 1210 may be a completely self-contained computing system,containing multiple cores or processors, a bus, memory controller,cache, etc. A multi-core processor may be symmetric or asymmetric.

To enable user interaction with the computing device 1200, an inputdevice 1245 can represent any number of input mechanisms, such as amicrophone for speech, a touch-sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, speech and so forth. An outputdevice 1235 can also be one or more of a number of output mechanismsknown to those of skill in the art. In some instances, multimodalsystems can enable a user to provide multiple types of input tocommunicate with the computing device 1200. The communications interface1240 can generally govern and manage the user input and system output.There is no restriction on operating on any particular hardwarearrangement and therefore the basic features here may easily besubstituted for improved hardware or firmware arrangements as they aredeveloped.

Storage device 1230 is a non-volatile memory and can be a hard disk orother types of computer readable media which can store data that areaccessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs) 1225, read only memory (ROM) 1220, andhybrids thereof.

The storage device 1230 can include services 1232, 1234, 1236 forcontrolling the processor 1210. Other hardware or software modules arecontemplated. The storage device 1230 can be connected to the systemconnection 1205. In one aspect, a hardware module that performs aparticular function can include the software component stored in acomputer-readable medium in connection with the necessary hardwarecomponents, such as the processor 1210, connection 1205, output device1235, and so forth, to carry out the function.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

In some embodiments the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, rackmount devices, standalone devices, and so on.Functionality described herein also can be embodied in peripherals oradd-in cards. Such functionality can also be implemented on a circuitboard among different chips or different processes executing in a singledevice, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims.

Claim language reciting “at least one of” refers to at least one of aset and indicates that one member of the set or multiple members of theset satisfy the claim. For example, claim language reciting “at leastone of A and B” means A, B, or A and B.

What is claimed is:
 1. A computer-implemented method comprising:querying a network controller to identify a configured static endpointin a logical model of a network; retrieving, from one or more nodes inthe network, endpoint information for a set of connected endpoints inthe network; determining that the endpoint information does not includethe configured static endpoint in the set of connected endpoints; andidentifying a first static endpoint inconsistency between the logicalmodel and the endpoint information based on the endpoint information notincluding the configured static endpoint in the set of connectedendpoints.
 2. The computer-implemented method of claim 1, furthercomprising generating an event specifying the first static endpointinconsistency.
 3. The computer-implemented method of claim 2, whereinthe event is associated with a severity level and an event type, andwherein the event type specifies the first static endpointinconsistency.
 4. The computer-implemented method of claim 1, furthercomprising providing, based on the first static endpoint inconsistency,a user interface comprising network status information.
 5. Thecomputer-implemented method of claim 4, further comprising: calculating,based on the first static endpoint inconsistency, a health score for oneor more endpoints in the network, wherein the network status informationcomprises the health score for the one or more endpoints.
 6. Thecomputer-implemented method of claim 1, wherein the one or more nodes inthe network includes at least one of a leaf node or a spine node.
 7. Thecomputer-implemented method of claim 1, further comprising: determining,when the endpoint information includes the configured static endpoint inthe set of connected endpoints, that a static flag in the endpointinformation is not set for the configured static endpoint; andidentifying a flag inconsistency based on the static flag in theendpoint information not being set for the configured static endpoint.8. The computer-implemented method of claim 1, wherein the network is asoftware-defined network (SDN).
 9. The computer-implemented method ofclaim 1, further comprising: determining that the set of connectedendpoints includes a static endpoint that is not found in the logicalmodel; and identifying a second static endpoint inconsistency based onthe set of connected endpoints including the static endpoint that is notfound in the logical model.
 10. A system comprising: one or moreprocessors; and at least one computer-readable storage medium havingstored therein instructions which, when executed by the one or moreprocessors, cause the system to: retrieve endpoint information from oneor more nodes in the network; identify a connected static endpoint inthe endpoint information based on a static flag for the connected staticendpoint being set; query a network controller to make a determinationthat the connected static endpoint does not have a corresponding staticendpoint in the logical model of the network; and identify a firststatic endpoint inconsistency based on the determination.
 11. The systemof claim 10, wherein the instructions further cause the system to: querythe network controller to identify a configured static endpoint in thelogical model of a network; determining that the endpoint informationdoes not include the configured static endpoint; and identifying asecond static endpoint inconsistency between the logical model and theendpoint information based on the endpoint information not including theconfigured static endpoint.
 12. The system of claim 10, wherein theinstructions further cause the system to generate an event specifyingthe first static endpoint inconsistency.
 13. The system of claim 12,wherein the event is associated with a severity level and an event type,and wherein the event type specifies the first static endpointinconsistency.
 14. The system of claim 10, wherein the instructionsfurther cause the system to provide, based on the first static endpointinconsistency, a user interface comprising network status information.15. The system of claim 14, wherein the instructions further cause thesystem to: calculate, based on the first static endpoint inconsistency,a health score for one or more endpoints in the network, wherein thenetwork status information comprises the health score for the one ormore endpoints.
 16. A non-transitory computer-readable medium comprisinginstructions stored therein which, when executed by one or moreprocessors, cause the one or more processors to: retrieving, from anetwork controller, a configured static endpoint information in alogical model of a network; retrieve, from one or more nodes in thenetwork, connected static endpoint information; determining that thereis an inconsistency based on a comparison of the configured staticendpoint information and the connected static endpoint information; andgenerating an event specifying the inconsistency.
 17. The non-transitorycomputer-readable medium of claim 16, wherein the instructions furthercause the one or more processors to provide, based on the event, a userinterface comprising network status information.
 18. The non-transitorycomputer-readable medium of claim 17, wherein the instructions furthercause the one or more processors to: calculate, based on the event, ahealth score for one or more endpoints in the network, wherein thenetwork status information comprises the health score for the one ormore endpoints.
 19. The non-transitory computer-readable medium of claim16, wherein the configured static endpoint information includes aconfigured static endpoint, and wherein the instructions further causethe one or more processors to: determine that the connected staticendpoint information does not include an entry corresponding to theconfigured static endpoint.
 20. The non-transitory computer-readablemedium of claim 16, wherein the connected static endpoint informationincludes a connected static endpoint, and wherein the instructionsfurther cause the one or more processors to: determine that theconfigured static endpoint information does not include an entrycorresponding to the connected static endpoint.